Research firm Gartner Inc. predicts that by 2016, 25 percent of large global companies will have adopted big data analytics for at least one security or fraud detection use case, up from 8 percent today, and will achieve a positive return on investment within the first six months of implementation.
Big data analytics gives enterprises faster access to their own data than ever, says Avivah Litan, vice president and distinguished analyst at Gartner. Litan says enterprises can achieve significant savings in time and money when using big data analytics to stop crime and security infractions, by stopping losses and increasing productivity.
Big data analytics enables enterprises to combine and correlate external and internal information to get a bigger picture of threats against their organizations, Litan says. It is applicable in many security and fraud cases, such as detection of advanced threats, insider threats and account takeover.
Information needed to uncover security events loses value over time, and timely intelligent data analysis is critical, Litan says. With big data analytics, enterprises can cut down on false alerts in existing monitoring systems by enriching them with contextual data and applying smarter analytics. This is especially important as the number of security events increase substantially year over year, she says.
Big data also lets organizations correlate high-priority alerts across monitoring systems to detect patterns of abuse and fraud, and get a big picture on the security state of the enterprise, Litan says.